regret bound

The Price of Knowledge: Optimal Algorithms for Costly Bandits UAI 2026 Toward Simultaneously Optimal Regret in U-Calibration COLT 2026 Truly Adapting to Adversarial Constraints in Constrained MABs COLT 2026 Unified Framework of Distributional Regret in Multi-Armed Bandits and Reinforcement Learning COLT 2026 Universal priors: solving empirical Bayes via Bayesian inference and pretraining COLT 2026 Wasserstein Policy Learning for Distributional Outcomes COLT 2026 Weighted Sequential Bayesian Inference for Non-Stationary Linear Contextual Bandits UAI 2026 What Capable Agents Must Know: Selection Theorems for Robust Decision-Making under Uncertainty UAI 2026 Achieving Õ(√T) Regret in Average-Reward POMDPs with Known Observation Models AISTATS 2025 A Computationally Efficient Algorithm for Infinite-Horizon Average-Reward Linear MDPs ICML 2025 ADAM Optimization with Adaptive Batch Selection ICLR 2025 Adaptive Market Making with Inventory Constraints via Online Learning AAAI 2025 Adjusted Expected Improvement for Cumulative Regret Minimization in Noisy Bayesian Optimization JMLR 2025 A Hybrid Weighted Nearest Neighbour Classifier for Semi-Supervised Learning JMLR 2025 Almost Optimal Batch-Regret Tradeoff for Batch Linear Contextual Bandits ICLR 2025 A Multi-Armed Bandit Approach to Online Selection and Evaluation of Generative Models AISTATS 2025 An Online Learning Theory of Trading-Volume Maximization ICLR 2025 A Polynomial-time Algorithm for Online Sparse Linear Regression with Improved Regret Bound under Weaker Conditions COLT 2025 Approximate Thompson Sampling for Learning Linear Quadratic Regulators with O(√T) Regret L4DC 2025 A Safe Bayesian Learning Algorithm for Constrained MDPs with Bounded Constraint Violation AISTATS 2025 Asymptotically Optimal Problem-Dependent Bandit Policies for Transfer Learning ACML 2025 A Theoretical Framework for Partially-Observed Reward States in RLHF ICLR 2025 A Tight Regret Analysis of Non-Parametric Repeated Contextual Brokerage AISTATS 2025 A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs JMLR 2025 Bandit Learning in Matching Markets with Indifference ICLR 2025